Background

Background information on the dataset…


Additional links or sources…

Data

Code for obtaining data…
library(tidyverse)
library(tidytuesdayR)
NFL_Data <-tidytuesdayR::tt_load("2018-08-28")
nfl_stats <- NFL_Data$`nfl_2010-2017`
glimpse(nfl_stats)
Rows: 81,525
Columns: 23
$ ...1         <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ name         <chr> "Duce Staley", "Lamar Smith", "Tiki Barber", "Stephen Dav…
$ team         <chr> "PHI", "MIA", "NYG", "WAS", "IND", "BAL", "NYJ", "MIN", "…
$ game_year    <dbl> 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 200…
$ game_week    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ rush_att     <dbl> 26, 27, 13, 23, 28, 27, 30, 14, 15, 10, 20, 13, 23, 14, 2…
$ rush_yds     <dbl> 201, 145, 144, 133, 124, 119, 110, 109, 88, 87, 84, 80, 7…
$ rush_avg     <dbl> 7.7, 5.4, 11.1, 5.8, 4.4, 4.4, 3.7, 7.8, 5.9, 8.7, 4.2, 6…
$ rush_tds     <dbl> 1, 1, 2, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 3, …
$ rush_fumbles <dbl> 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 2, 0, 1, 1, …
$ rec          <dbl> 4, 1, 3, 4, 6, 4, 6, 2, 2, NA, 4, 3, 1, 4, 1, 1, 1, NA, N…
$ rec_yds      <dbl> 61, 12, 25, 37, 40, 32, 34, 3, 20, NA, 29, 10, -2, 100, 1…
$ rec_avg      <dbl> 15.3, 12.0, 8.3, 9.3, 6.7, 8.0, 5.7, 1.5, 10.0, NA, 7.3, …
$ rec_tds      <dbl> 0, 0, 0, 0, 1, 0, 1, 0, 0, NA, 0, 0, 0, 1, 0, 0, 0, NA, N…
$ rec_fumbles  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, NA, N…
$ pass_att     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 41, NA, NA, NA, NA, N…
$ pass_yds     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 290, NA, NA, NA, NA, …
$ pass_tds     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA…
$ int          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA…
$ sck          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA…
$ pass_fumbles <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA…
$ rate         <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 102.7, NA, NA, NA, NA…
$ position     <chr> "RB", "RB", "RB", "RB", "RB", "RB", "RB", "RB", "RB", "QB…
hi_rsh <- filter(nfl_stats, rush_yds > 200) %>% 
    select(name, rush_yds, starts_with("game"))
hi_rsh %>% 
    count(game_year)
# A tibble: 17 × 2
   game_year     n
       <dbl> <int>
 1      2000    10
 2      2001     2
 3      2002     4
 4      2003     3
 5      2004     2
 6      2005     3
 7      2006     4
 8      2007     3
 9      2008     2
10      2009     5
# … with 7 more rows
glimpse(nfl_stats)
Rows: 81,525
Columns: 23
$ ...1         <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ name         <chr> "Duce Staley", "Lamar Smith", "Tiki Barber", "Stephen Dav…
$ team         <chr> "PHI", "MIA", "NYG", "WAS", "IND", "BAL", "NYJ", "MIN", "…
$ game_year    <dbl> 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 200…
$ game_week    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ rush_att     <dbl> 26, 27, 13, 23, 28, 27, 30, 14, 15, 10, 20, 13, 23, 14, 2…
$ rush_yds     <dbl> 201, 145, 144, 133, 124, 119, 110, 109, 88, 87, 84, 80, 7…
$ rush_avg     <dbl> 7.7, 5.4, 11.1, 5.8, 4.4, 4.4, 3.7, 7.8, 5.9, 8.7, 4.2, 6…
$ rush_tds     <dbl> 1, 1, 2, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 3, …
$ rush_fumbles <dbl> 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 2, 0, 1, 1, …
$ rec          <dbl> 4, 1, 3, 4, 6, 4, 6, 2, 2, NA, 4, 3, 1, 4, 1, 1, 1, NA, N…
$ rec_yds      <dbl> 61, 12, 25, 37, 40, 32, 34, 3, 20, NA, 29, 10, -2, 100, 1…
$ rec_avg      <dbl> 15.3, 12.0, 8.3, 9.3, 6.7, 8.0, 5.7, 1.5, 10.0, NA, 7.3, …
$ rec_tds      <dbl> 0, 0, 0, 0, 1, 0, 1, 0, 0, NA, 0, 0, 0, 1, 0, 0, 0, NA, N…
$ rec_fumbles  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, NA, N…
$ pass_att     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 41, NA, NA, NA, NA, N…
$ pass_yds     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 290, NA, NA, NA, NA, …
$ pass_tds     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA…
$ int          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA…
$ sck          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA…
$ pass_fumbles <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA…
$ rate         <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 102.7, NA, NA, NA, NA…
$ position     <chr> "RB", "RB", "RB", "RB", "RB", "RB", "RB", "RB", "RB", "QB…
hi_pass <-filter(nfl_stats, pass_yds > 500) %>% 
    select(name, pass_yds, starts_with("game"))
hi_pass %>% 
    count(game_year)
# A tibble: 10 × 2
   game_year     n
       <dbl> <int>
 1      2000     1
 2      2006     1
 3      2009     1
 4      2011     1
 5      2012     2
 6      2013     1
 7      2014     1
 8      2015     2
 9      2016     2
10      2017     1
glimpse(nfl_stats)
Rows: 81,525
Columns: 23
$ ...1         <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
$ name         <chr> "Duce Staley", "Lamar Smith", "Tiki Barber", "Stephen Dav…
$ team         <chr> "PHI", "MIA", "NYG", "WAS", "IND", "BAL", "NYJ", "MIN", "…
$ game_year    <dbl> 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 200…
$ game_week    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
$ rush_att     <dbl> 26, 27, 13, 23, 28, 27, 30, 14, 15, 10, 20, 13, 23, 14, 2…
$ rush_yds     <dbl> 201, 145, 144, 133, 124, 119, 110, 109, 88, 87, 84, 80, 7…
$ rush_avg     <dbl> 7.7, 5.4, 11.1, 5.8, 4.4, 4.4, 3.7, 7.8, 5.9, 8.7, 4.2, 6…
$ rush_tds     <dbl> 1, 1, 2, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 3, …
$ rush_fumbles <dbl> 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 2, 0, 1, 1, …
$ rec          <dbl> 4, 1, 3, 4, 6, 4, 6, 2, 2, NA, 4, 3, 1, 4, 1, 1, 1, NA, N…
$ rec_yds      <dbl> 61, 12, 25, 37, 40, 32, 34, 3, 20, NA, 29, 10, -2, 100, 1…
$ rec_avg      <dbl> 15.3, 12.0, 8.3, 9.3, 6.7, 8.0, 5.7, 1.5, 10.0, NA, 7.3, …
$ rec_tds      <dbl> 0, 0, 0, 0, 1, 0, 1, 0, 0, NA, 0, 0, 0, 1, 0, 0, 0, NA, N…
$ rec_fumbles  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, NA, N…
$ pass_att     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 41, NA, NA, NA, NA, N…
$ pass_yds     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 290, NA, NA, NA, NA, …
$ pass_tds     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA…
$ int          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA…
$ sck          <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA…
$ pass_fumbles <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA…
$ rate         <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, 102.7, NA, NA, NA, NA…
$ position     <chr> "RB", "RB", "RB", "RB", "RB", "RB", "RB", "RB", "RB", "QB…
hi_rec <-filter(nfl_stats, rec_yds > 200) %>% 
    select(name, pass_yds, starts_with("game"))
hi_pass %>% 
    count(game_year)
# A tibble: 10 × 2
   game_year     n
       <dbl> <int>
 1      2000     1
 2      2006     1
 3      2009     1
 4      2011     1
 5      2012     2
 6      2013     1
 7      2014     1
 8      2015     2
 9      2016     2
10      2017     1

Information about the dataset…

Graphs


Code for creating graphs…

labs_grp_bubble <- labs(
    title = "Rushing Attempts Leaders",
    x = "Year", y = "Name", 
    size = "Rushing Yards")

ggp2_grp_bubble <- filter(nfl_stats, 
                  rush_att > 33) |> 
    ggplot(aes(
        x = game_year, 
        y = name)) + 
    geom_point(
        aes(size = rush_yds,
            fill= name), 
        show.legend = FALSE,
        alpha = 2/3, 
        shape = 21, 
        color = "black") +
   scale_size(range = c(1,7), 
        name = "rushing yards")+
    ggthemes::theme_few(
      base_size = 11)

#color is a fill=rush_yds inside the AES funtcion

ggp2_grp_bubble + 
    labs_grp_bubble

Graphs

labs_scatter <- labs(
    title = "Highest Rushers",
    x = "game_year", y = "name)")
ggp2_scatter <- filter(nfl_stats, rush_yds > 200)|>
    ggplot(
        aes(x = game_year, 
            y = name)) +
    geom_point()

ggp2_scatter + 
    labs_scatter

Graphs

labs_grp_bubble <- labs(
    title = "Receptions >15",
    x = "Year", y = "Name", 
    size = "Rushing Yards")

ggp2_grp_bubble <- filter(nfl_stats, rec  > 12) |> 
    ggplot(aes(
        x = game_year, y = name)) + 
    geom_point(
        aes(size = rush_yds, fill= name), 
        show.legend = FALSE,
        alpha = 2/3, shape = 21, color = "black") +
   scale_size(range = c(1,7), name = "rushing yards")+
    ggthemes::theme_few()

#color is a fill=rush_yds inside the AES funtcion

ggp2_grp_bubble + 
    labs_grp_bubble

Graphs

labs_scatter <- labs(
    title = "Highest Recivers",
    x = "game_year", y = "name)")
ggp2_scatter <- filter(nfl_stats, rec_yds > 200)|>
    ggplot(
        aes(x = game_year, 
            y = name)) +
    geom_point()

ggp2_scatter + 
    labs_scatter

Graphs

labs_grp_bubble <- labs(
    title = "Pass Attempt Leaders",
    x = "Year", y = "Name", 
    size = "Rushing Yards")

ggp2_grp_bubble <- filter(nfl_stats, pass_att  > 55) |> 
    ggplot(aes(
        x = game_year, y = name)) + 
    geom_point(
        aes(size = rush_yds, fill= name), 
        show.legend = FALSE,
        alpha = 2/3, shape = 21, color = "black") +
   scale_size(range = c(1,7), name = "rushing yards")+
    ggthemes::theme_few()

#color is a fill=rush_yds inside the AES funtcion

ggp2_grp_bubble + 
    labs_grp_bubble

Graphs

labs_scatter <- labs(
    title = "Highest Passers",
    x = "game_year", y = "name)")
ggp2_scatter <- filter(nfl_stats, pass_yds > 500)|>
    ggplot(
        aes(x = game_year, 
            y = name)) +
    geom_point()

ggp2_scatter + 
    labs_scatter


Graphs for data…